An Overview of Data Privacy in Multi-Agent Learning Systems
Kato Mivule, Darsana P. Josyula, Claude Turner · 2013
Abstract — Public and private sector entities continuously produce, store, and transact in large amounts of data. However, combined with the growth of the internet, such datasets get stored and accessed on multiple devices, locations, and across the globe. Therefore, the necessity for autonomous agents that can learn across distributed systems to extract knowledge from large datasets while at the same time taking into account data privacy considerations while interacting with other agents remains a challenge. In this paper, we endeavor to provide an overview of data privacy in multi-agent learning systems, while at the same time highlighting current challenges and future areas of work and research.